The jackknife estimate of variance of a Kaplan-Meier integral

Abstract

Let $\hat{F}_n$ be the Kaplan-Meier estimator of a distribution function F computed from randomly censored data. It is known that, under certain integrability assumptions on a function $\varphi$, the Kaplan-Meier integral $\int \varphi d \hat{F}_n$, when properly standardized, is asymptotically normal. In this paper it is shown that, with probability 1, the jackknife estimate of variance consistently estimates the (limit) variance.